#!/usr/bin/env python
import time
import sys
sys.path.insert(0, '../Tools')
import leech as model
import tools as tl
import window as win
import multiprocessing as mp
import numpy as np
import pylab as pl
from matplotlib import animation
class traces(win.window):
title = 'Membrane Voltage Traces (Oscilloscope)'
figsize = (16, 4)
def __init__(self, system, network, info=None, position=None):
win.window.__init__(self, position)
self.system = system
self.network = network
self.info = info
self.CYCLES = 8
self.state = system.load_initial_condition( pl.rand(), pl.rand() )
self.initial_condition = self.system.load_initial_condition(pl.rand(), pl.rand())
self.running = False
self.pulsed = 0
self.ax = self.fig.add_subplot(111, frameon=False, yticks=[])
self.li_b, = self.ax.plot([], [], 'b-', lw=1.)
self.li_g, = self.ax.plot([], [], 'g-', lw=1.)
self.li_r, = self.ax.plot([], [], 'r-', lw=1.)
self.ax.set_xlabel(r'time (sec.)', fontsize=20)
self.ax.set_xticklabels(np.arange(0., 1., 0.1), fontsize=15)
self.ax.set_yticklabels(np.arange(0., 1., 0.1), fontsize=15)
self.ax.set_xlim(0., 100.)
self.ax.set_ylim(-0.06-0.12, 0.04)
self.key_func_dict.update(u=traces.increase_cycles, i=traces.decrease_cycles)
#self.fig.canvas.mpl_connect('button_press_event', self.on_click)
self.fig.canvas.mpl_connect('axes_enter_event', self.focus_in)
def adjust_cycles(self, adjustment):
self.CYCLES = adjustment
self.computeTraces()
self.focus_in()
def increase_cycles(self):
self.adjust_cycles(self.CYCLES+1)
def decrease_cycles(self):
self.adjust_cycles(self.CYCLES-1*(self.CYCLES>0))
def focus_in(self, event=None):
descriptor = "CYCLES : "+str(self.CYCLES)+" ('u' > 'i')"
if self.info is None: print descriptor
else: self.info.set(descriptor)
def on_click(self, event):
if event.inaxes == self.ax and self.running == False:
self.params = model.params_three()
self.coupling = np.zeros((9), float)
self.coupling[:6] = self.network.coupling_strength
length = self.system.N_output(self.CYCLES)
self.t = self.system.dt*np.arange(length)
self.trajectory = np.zeros((length, 3), float)
self.li_b.set_data(self.t, self.trajectory[:, 0])
self.li_g.set_data(self.t, self.trajectory[:, 1]-0.06)
self.li_r.set_data(self.t, self.trajectory[:, 2]-0.12)
ticks = np.asarray(self.t[::self.t.size/10], dtype=int)
self.ax.set_xticks(ticks)
self.ax.set_xticklabels(ticks)
self.ax.set_xlim(self.t[0], self.t[-1])
self.fig.canvas.draw()
self.anim = animation.FuncAnimation(self.fig, self.compute_step, init_func=self.init, frames=self.trajectory.shape[0], interval=0, blit=True, repeat=False)
self.running = True
def init(self):
self.li_b.set_data([], [])
self.li_g.set_data([], [])
self.li_r.set_data([], [])
return self.li_b, self.li_g, self.li_r
def compute_step(self, idx):
model.step_three_rk4(
self.state, self.params, self.coupling,
self.system.dt/float(self.system.stride),
self.system.stride)
self.trajectory[idx, :] = self.state[::model.N_EQ1]
if self.pulsed:
self.trajectory[idx-1, self.pulsed-1] = -0.1
self.trajectory[idx, self.pulsed-1] = 0.1
self.pulsed = 0
self.li_b.set_data(self.t, self.trajectory[:, 0])
self.li_g.set_data(self.t, self.trajectory[:, 1]-0.06)
self.li_r.set_data(self.t, self.trajectory[:, 2]-0.12)
if idx == self.trajectory.shape[0]-1:
self.running = False
return self.li_b, self.li_g, self.li_r
def computeTraces(self, initial_condition=None, plotit=True):
if initial_condition is None:
initial_condition = self.initial_condition
V_i = model.integrate_three_rk4(
initial_condition,
self.network.coupling_strength,
self.system.dt/float(self.system.stride),
self.system.N_output(self.CYCLES),
self.system.stride)
t = self.system.dt*np.arange(V_i.shape[0])
if plotit:
ticks = np.asarray(t[::t.size/10], dtype=int)
self.li_b.set_data(t, V_i[:, 0])
self.li_g.set_data(t, V_i[:, 1]-0.06)
self.li_r.set_data(t, V_i[:, 2]-0.12)
self.ax.set_xticks(ticks)
self.ax.set_xticklabels(ticks)
self.ax.set_xlim(t[0], t[-1])
self.fig.canvas.draw()
return t, V_i
if __name__ == "__main__":
import system as sys
import network as netw
s = sys.system()
n = netw.network()
tra = traces(s, n)
pl.show()
